title: Variations in predicted risks in personal genome testing for common complex diseases.
abstract: OBJECTIVE
  The promise of personalized genomics for common complex diseases depends, in part, on the ability to predict genetic risks on the basis of single nucleotide polymorphisms. We examined and compared the methods of three companies (23andMe, deCODEme, and Navigenics) that have offered direct-to-consumer personal genome testing.
  
  
  METHODS
  We simulated genotype data for 100,000 individuals on the basis of published genotype frequencies and predicted disease risks using the methods of the companies. Predictive ability for six diseases was assessed by the AUC.
  
  
  RESULTS
  AUC values differed among the diseases and among the companies. The highest values of the AUC were observed for age-related macular degeneration, celiac disease, and Crohn disease. The largest difference among the companies was found for celiac disease: the AUC was 0.73 for 23andMe and 0.82 for deCODEme. Predicted risks differed substantially among the companies as a result of differences in the sets of single nucleotide polymorphisms selected and the average population risks selected by the companies, and in the formulas used for the calculation of risks.
  
  
  CONCLUSIONS
  Future efforts to design predictive models for the genomics of common complex diseases may benefit from understanding the strengths and limitations of the predictive algorithms designed by these early companies.
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: Rachel R J
authors.initials: RR
authors.lastname: Kalf
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: Raluca
authors.initials: R
authors.lastname: Mihaescu
authors.affiliation: Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: Suman
authors.initials: S
authors.lastname: Kundu
authors.affiliation: Department of Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Peter
authors.initials: P
authors.lastname: de Knijff
authors.affiliation: Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Robert C
authors.initials: RC
authors.lastname: Green
authors.affiliation: 1] Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands [2] Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
authors.forename: A Cecile J W
authors.initials: AC
authors.lastname: Janssens
mesh_terms: D000465:Algorithms; D001281:Atrial Fibrillation / Q000175:diagnosis / Q000235:genetics; D002446:Celiac Disease / Q000175:diagnosis / Q000235:genetics; D003424:Crohn Disease / Q000175:diagnosis / Q000235:genetics; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D005820:Genetic Testing; D014644:Genetic Variation; D015894:Genome, Human; D005838:Genotype; D006801:Humans; D008268:Macular Degeneration / Q000175:diagnosis / Q000235:genetics; D008297:Male; D010548:Personal Health Services; D020641:Polymorphism, Single Nucleotide; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000235:genetics; D018570:Risk Assessment; D012307:Risk Factors